{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Assessing cluster correctness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn import datasets\n",
    "from sklearn import cluster\n",
    "\n",
    "blobs, ground_truth = datasets.make_blobs(1000, centers=3,cluster_std=1.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x9cc7f98>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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L0aq77qKrZs+m5UuXUktLS4/OU1tbS1OnTiWfz0clJSV0xRVX0BtvvEFEiVmOREQbN26k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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7a9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import datasets\n",
    "from sklearn import cluster\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    " \n",
    "f, ax = plt.subplots(figsize=(7, 5))\n",
    "colors = ['r', 'g', 'b']\n",
    "for i in range(3):\n",
    "     p = blobs[ground_truth == i]\n",
    "     ax.scatter(p[:,0], p[:,1], c=colors[i],\n",
    "     label=\"Cluster {}\".format(i))\n",
    "ax.set_title(\"Cluster With Ground Truth\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
       "    n_clusters=3, n_init=10, n_jobs=1, precompute_distances='auto',\n",
       "    random_state=None, tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans = cluster.KMeans(n_clusters=3)\n",
    "kmeans.fit(blobs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 7.39863797, -1.25523322],\n",
       "       [-7.83864566, -1.84072534],\n",
       "       [ 9.89662887, -7.66700011]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans.cluster_centers_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RVzM+pmm4JBhEVlHwZDKJu3fuNJZ5engYe3ftwnenpvDC6dOYLBTwiXvvRenc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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7a668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(7, 5))\n",
    "colors = ['r', 'g', 'b']\n",
    "for i in range(3): \n",
    "     p = blobs[ground_truth == i]\n",
    "     ax.scatter(p[:,0], p[:,1], c=colors[i], label=\"Cluster {}\".format(i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.994011976048\n",
      "1.0\n",
      "0.972972972973\n"
     ]
    }
   ],
   "source": [
    "for i in range(3):\n",
    "     print (kmeans.labels_ == ground_truth)[ground_truth == i].astype(int).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Not necessary here:\n",
    "\n",
    "new_ground_truth = ground_truth.copy()\n",
    "new_ground_truth[ground_truth == 1] = 2\n",
    "new_ground_truth[ground_truth == 2] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.95112595073820716"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import metrics\n",
    "metrics.normalized_mutual_info_score(ground_truth, kmeans.labels_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.normalized_mutual_info_score(ground_truth, ground_truth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.044837842275852"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.mutual_info_score(ground_truth, kmeans.labels_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5963.0968823764033"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans.inertia_"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
